A Doppler ultrasound clutter filter that enables estimation of low velocity blood flow could considerably improve ultrasound as a tool for clinical diagnosis and monitoring, including for the evaluation of vascular diseases and tumor perfusion. Conventional Doppler ultrasound is currently used for visualizing and estimating blood flow. However, conventional Doppler is limited by frame rate and tissue clutter caused by involuntary movement of the patient or sonographer. Spectral broadening of the clutter due to tissue motion limits ultrasound’s ability to detect blood flow less than about 5mm/s at an 8MHz center frequency. We propose a clutter filtering technique that may increase the sensitivity of Doppler measurements to at least as low as 0.41mm/s. The proposed filter uses an adaptive demodulation scheme that decreases the bandwidth of the clutter. To test the performance of the adaptive demodulation method at removing sonographer hand motion, six volunteer subjects acquired data from a basic quality assurance phantom. Additionally, to test initial in vivo feasibility, an arterial occlusion reactive hyperemia study was performed to assess the efficiency of the proposed filter at preserving signals from blood velocities 2mm/s or greater. The hand motion study resulted in initial average bandwidths of 577Hz (28.5mm/s), which were decreased to 7.28Hz (0.36mm/s) at -60 dB at 3cm using our approach. The in vivo power Doppler study resulted in 15.2dB and 0.15dB dynamic ranges between the lowest and highest blood flow time points for the proposed filter and conventional 50Hz high pass filter, respectively.

Chronic venous disease is a common condition leading to varicose veins, leg edema, post-thrombotic syndrome and venous ulcerations. Ultrasound (US) is the main modality for examination of venous disease. Color Doppler and occasionally spectral Doppler US (SDUS) are used for evaluation of the venous flow. Peak velocities measured by SDUS are rarely used in a clinical setting for evaluating chronic venous disease due to inadequate reproducibility mainly caused by the angle dependency of the estimate. However, estimations of blood velocities are of importance in characterizing venous disease. Transverse Oscillation US (TOUS), a non-invasive angle independent method, has been implemented on a commercial scanner. TOUS's advantage compared to SDUS is a more elaborate visualization of complex flow. The aim of this study was to evaluate, whether TOUS perform equal to SDUS for recording velocities in the veins of the lower limbs. Four volunteers were recruited for the study. A standardized flow was provoked with a cuff compression-decompression system placed around the lower leg. The average peak velocity in the popliteal vein of the four volunteers was 151.5 cm/s for SDUS and 105.9 cm/s for TOUS (p <0.001). The average of the peak velocity standard deviations (SD) were 17.0 cm/s for SDUS and 13.1 cm/s for TOUS (p <0.005). The study indicates that TOUS estimates lower peak velocity with improved SD when compared to SDUS. TOUS may be a tool for evaluation of venous disease providing quantitative measures for the evaluation of venous blood flow.

This work presents the first in vivo results of 2-D high frame rate vector velocity imaging for transthoracic cardiac imaging. Measurements are made on a healthy volunteer using the SARUS experimental ultrasound scanner connected to an intercostal phased-array probe. Two parasternal long-axis view (PLAX) are obtained, one centred at the aortic valve and another centred at the left ventricle. The acquisition sequence was composed of 3 diverging waves for high frame rate synthetic aperture flow imaging. For verification a phantom measurement is performed on a transverse straight 5 mm diameter vessel at a depth of 100 mm in a tissue-mimicking phantom. A flow pump produced a 2 ml/s constant flow with a peak velocity of 0.2 m/s. The average estimated flow angle in the ROI was 86.22° ± 6.66° with a true flow angle of 90°. A relative velocity bias of −39% with a standard deviation of 13% was found. In-vivo acquisitions show complex flow patterns in the heart. In the aortic valve view, blood is seen exiting the left ventricle cavity through the aortic valve into the aorta during the systolic phase of the cardiac cycle. In the left ventricle view, blood flow is seen entering the left ventricle cavity through the mitral valve and splitting in two ways when approximating the left ventricle wall. The work presents 2-D velocity estimates on the heart from a non-invasive transthoracic scan. The ability of the method detecting flow regardless of the beam angle could potentially reveal a more complete view of the flow patterns presented on the heart.

This paper presents an in-house developed 2-D capacitive micromachined ultrasonic transducer (CMUT) applied for 3-D blood flow estimation. The probe breaks with conventional transducers in two ways; first, the ultrasonic pressure field is generated from thousands of small vibrating micromachined cells, and second, elements are accessed by row and/or column indices. The 62+62 2-D row-column addressed prototype CMUT probe was used for vector flow estimation by transmitting focused ultrasound into a flow-rig with a fully developed parabolic flow. The beam-to-flow angle was 90°. The received data was beamformed and processed offline. A transverse oscillation (TO) velocity estimator was used to estimate the 3-D vector flow along a line originating from the center of the transducer. The estimated velocities in the lateral and axial direction were close to zero as expected. In the transverse direction a characteristic parabolic velocity profile was estimated with a peak velocity of 0.48 m/s ± 0.02 m/s in reference to the expected 0.54 m/s. The results presented are the first 3-D vector flow estimates obtained with a row-column CMUT probe, which demonstrates that the CMUT technology is feasible for 3-D flow estimation.

Image registration techniques using free-form deformation models have shown promising results for 3D myocardial strain estimation from ultrasound. However, the use of this technique has mostly been limited to research institutes due to the high computational demand, which is primarily due to the computational load of the regularization term ensuring spatially smooth cardiac strain estimates. Indeed, this term typically requires evaluating derivatives of the transformation field numerically in each voxel of the image during every iteration of the optimization process. In this paper, we replace this time-consuming step with a closed-form solution directly associated with the transformation field resulting in a speed up factor of ~10-60,000, for a typical 3D B-mode image of 2503 and 5003 voxels, depending upon the size and the parametrization of the transformation field. The performance of the numeric and the analytic solutions was contrasted by computing tracking and strain accuracy on two realistic synthetic 3D cardiac ultrasound sequences, mimicking two ischemic motion patterns. Mean and standard deviation of the displacement errors over the cardiac cycle for the numeric and analytic solutions were 0.68±0.40 mm and 0.75±0.43 mm respectively. Correlations for the radial, longitudinal and circumferential strain components at end-systole were 0.89, 0.83 and 0.95 versus 0.90, 0.88 and 0.92 for the numeric and analytic regularization respectively. The analytic solution matched the performance of the numeric solution as no statistically significant differences (p>0.05) were found when expressed in terms of bias or limits-of-agreement.

Breast cancer is one of the most common cancer types accounting for 29% of all cancer cases. Early detection and treatment has a crucial impact on improving the survival of affected patients. Ultrasound (US) is non-ionizing, portable, inexpensive, and real-time imaging modality for screening and quantifying breast cancer. Due to these attractive attributes, the last decade has witnessed many studies on using quantitative ultrasound (QUS) methods in tissue characterization. However, these studies have mainly been limited to 2-D QUS methods using hand-held US (HHUS) scanners. With the availability of automated breast ultrasound (ABUS) technology, this study is the first to develop 3-D QUS methods for the ABUS visualization of breast tumours. Using an ABUS system, unlike the manual 2-D HHUS device, the whole patient’s breast was scanned in an automated manner. The acquired frames were subsequently examined and a region of interest (ROI) was selected in each frame where tumour was identified. Standard 2-D QUS methods were used to compute spectral and backscatter coefficient (BSC) parametric maps on the selected ROIs. Next, the computed 2-D parameters were mapped to a Cartesian 3-D space, interpolated, and rendered to provide a transparent color-coded visualization of the entire breast tumour. Such 3-D visualization can potentially be used for further analysis of the breast tumours in terms of their size and extension. Moreover, the 3-D volumetric scans can be used for tissue characterization and the categorization of breast tumours as benign or malignant by quantifying the computed parametric maps over the whole tumour volume.

In recent years, many research studies have been carried out on ultrasound computed tomography (USCT) for its application prospect in early diagnosis of breast cancer. This paper applies four kinds of coherence-factor-like beamforming methods to improve the image quality of synthetic aperture focusing method for USCT, including the coherence-factor (CF), the phase coherence factor (PCF), the sign coherence factor (SCF) and the spatial smoothing coherence factor (SSCF) (proposed in our previous work). The performance of these methods was tested with simulated raw data which were generated by the ultrasound simulation software PZFlex 2014. The simulated phantom was set to be water of 4cm diameter with three nylon objects of different diameters inside. The ring-type transducer had 72 elements with a center frequency of 1MHz. The results show that all the methods can reveal the biggest nylon circle with the radius of 2.5mm. SSCF gets the highest SNR among the proposed methods and provides a more homogenous background. None of these methods can reveal the two smaller nylon circles with the radius of 0.75mm and 0.25mm. This may be due to the small number of elements.

In our first clinical study with a full 3D Ultrasound Computer Tomography (USCT) system patient data was acquired in eight minutes for one breast. In this paper the patient movement during the acquisition was analyzed quantitatively and as far as possible corrected in the resulting images. The movement was tracked in ten successive reflectivity reconstructions of full breast volumes acquired during 10 s intervals at different aperture positions, which were separated by 41 s intervals. The mean distance between initial and final position was 2.2 mm (standard deviation (STD) ± 0.9 mm, max. 4.1 mm, min. 0.8 mm) and the average sum of all moved distances was 4.9 mm (STD ± 1.9 mm, max. 8.8 mm, min. 2.7 mm). The tracked movement was corrected by summing successive images, which were transformed according to the detected movement. The contrast of these images increased and additional image content became visible.

Ultrasound Computer Tomography (USCT) is a promising new imaging method for breast cancer diagnosis. We developed a 3D USCT system and tested it in a pilot study with encouraging results: 3D USCT was able to depict two carcinomas, which were present in contrast enhanced MRI volumes serving as ground truth. To overcome severe differences in the breast shape, an image registration was applied. We analyzed the correlation between average sound speed in the breast and the breast density estimated from segmented MRIs and found a positive correlation with R=0.70. Based on the results of the pilot study we now carry out a successive clinical study with 200 patients. For this we integrated our reconstruction methods and image post-processing into a comprehensive workflow. It includes a dedicated DICOM viewer for interactive assessment of fused USCT images. A new preview mode now allows intuitive and faster patient positioning. We updated the USCT system to decrease the data acquisition time by approximately factor two and to increase the penetration depth of the breast into the USCT aperture by 1 cm. Furthermore the compute-intensive reflectivity reconstruction was considerably accelerated, now allowing a sub-millimeter volume reconstruction in approximately 16 minutes. The updates made it possible to successfully image first patients in our ongoing clinical study.

Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.

Ultrasound waveform tomography techniques have shown promising results for the visualization and characterization of breast disease. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, we have previously reconstructed the sound speed distributions of breasts of varying densities with different types of breast disease including benign and malignant lesions. By allowing the sound speed to have an imaginary component, we can model the intrinsic attenuation of a medium. We can similarly recover the imaginary component of the velocity and thus the attenuation. In this paper, we will briefly review ultrasound waveform tomography techniques, discuss attenuation and its relations to the imaginary component of the sound speed, and provide both numerical and ex vivo examples of waveform tomography attenuation reconstructions.

In this paper, we present an automatic solution for segmentation and quantification of the left atrium (LA) from 3D cardiac ultrasound. A model-based framework is applied, making use of (deformable) active surfaces to model the endocardial surfaces of cardiac chambers, allowing incorporation of a priori anatomical information in a simple fashion. A dual-chamber model (LA and left ventricle) is used to detect and track the atrio-ventricular (AV) plane, without any user input. Both chambers are represented by parametric surfaces and a Kalman filter is used to fit the model to the position of the endocardial walls detected in the image, providing accurate detection and tracking during the whole cardiac cycle. This framework was tested in 20 transthoracic cardiac ultrasound volumetric recordings of healthy volunteers, and evaluated using manual traces of a clinical expert as a reference. The 3D meshes obtained with the automatic method were close to the reference contours at all cardiac phases (mean distance of 0.03±0.6 mm). The AV plane was detected with an accuracy of −0.6±1.0 mm. The LA volumes assessed automatically were also in agreement with the reference (mean ±1.96 SD): 0.4±5.3 ml, 2.1±12.6 ml, and 1.5±7.8 ml at end-diastolic, end-systolic and pre-atrial-contraction frames, respectively. This study shows that the proposed method can be used for automatic volumetric assessment of the LA, considerably reducing the analysis time and effort when compared to manual analysis.

The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific
community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic
orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence
between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left
ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain
assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is
presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation
of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° ± 18, 50° was found, whereas
the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only
occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment,
which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation
of the segmented left ventricle is proposed.

Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean±SD) 4.3±1.2 mm compared to a reference error of 2.8 ± 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 ± 11.6 ms for Aortic Valve (AV) opening, 18.6 ± 16.0 ms for AV closing, and 34.6 ± 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms.

Biomechanical properties of soft tissues can provide information regarding the local health status. Often the cells in pathological tissues can be found to form a stiff extracellular environment, which is a sensitive, early diagnostic indicator of disease. Quasi-static ultrasonic elasticity imaging provides a way to image the mechanical properties of tissues. Strain images provide a map of the relative tissue stiffness, but ambiguities and artifacts limit its diagnostic value. Accurately mapping intrinsic mechanical parameters of a region may increase diagnostic specificity. However, the inverse problem, whereby force and displacement estimates are used to estimate a constitutive matrix, is ill conditioned. Our method avoids many of the issues involved with solving the inverse problem, such as unknown boundary conditions and incomplete information about the stress field, by building an empirical model directly from measured data. Surface force and volumetric displacement data gathered during imaging are used in conjunction with the AutoProgressive method to teach artificial neural networks the stress-strain relationship of tissues. The Autoprogressive algorithm has been successfully used in many civil engineering applications and to estimate ocular pressure and corneal stiffness; here, we are expanding its use to any tissues imaged ultrasonically. We show that force-displacement data recorded with an ultrasound probe and displacements estimated at a few points in the imaged region can be used to estimate the full stress and strain vectors throughout an entire model while only assuming conservation laws. We will also demonstrate methods to parameterize the mechanical properties based on the stress-strain response of trained neural networks. This method is a fundamentally new approach to medical elasticity imaging that for the first time provides full stress and strain vectors from one set of observation data.

Microbubble-based contrast agents are commonly used in ultrasound imaging to help differentiate the blood pool from the endocardial wall. It is essential to use an agent which produces high image intensity relative to the surrounding tissue, commonly referred to contrast effect. When exposed to ultrasound waves, microbubbles produce an intense backscatter signal in addition to the contrast produced by the fluctuating size of the microbubbles. However, over time, the microbubble concentration depletes, leading to reduced visual enhancement. The retention time associated with contrast effect varies according to the frequency and power level of the ultrasound wave, as well as the contrast agent used. The primary objective of this study was to investigate and identify the most appropriate image acquisition parameters that render optimal contrast effect for two intravenous contrast agents, Optison™ and Definity™. Several controlled in vitro experiments were conducted using an experimental apparatus that featured a perfused tissue-emulating phantom. A continuous flow of contrast agent was imaged using ultrasound at different frequencies and power levels, while a pulse wave Doppler device was used to monitor the concentration of the contrast agent solution. The contrast effect was determined based on the image intensity inside the flow pipe mimicking the blood-pool relative to the intensity of the surrounding phantom material mimicking cardiac tissue. To identify the combination of parameters that yielded optimal visualization for each contrast agent tested, the contrast effect was assessed at different microbubble concentrations and different ultrasound imaging frequencies and transmission power levels.

High-dose-rate (HDR) interstitial brachytherapy is often included in standard-of-care for gynaecological cancers. Needles are currently inserted through a perineal template without any standard real-time imaging modality to assist needle guidance, causing physicians to rely on pre-operative imaging, clinical examination, and experience. While two-dimensional (2D) ultrasound (US) is sometimes used for real-time guidance, visualization of needle placement and depth is difficult and subject to variability and inaccuracy in 2D images. The close proximity to critical organs, in particular the rectum and bladder, can lead to serious complications. We have developed a three-dimensional (3D) transrectal US system and are investigating its use for intra-operative visualization of needle positions used in HDR gynaecological brachytherapy. As a proof-of-concept, four patients were imaged with post-insertion 3D US and x-ray CT. Using software developed in our laboratory, manual rigid registration of the two modalities was performed based on the perineal template’s vaginal cylinder. The needle tip and a second point along the needle path were identified for each needle visible in US. The difference between modalities in the needle trajectory and needle tip position was calculated for each identified needle. For the 60 needles placed, the mean trajectory difference was 3.23 ± 1.65° across the 53 visible needle paths and the mean difference in needle tip position was 3.89 ± 1.92 mm across the 48 visible needles tips. Based on the preliminary results, 3D transrectal US shows potential for the development of a 3D US-based needle guidance system for interstitial gynaecological brachytherapy.

This paper presents a method for measuring pressure changes in deep-tissue vessels using vector velocity ultrasound data. The large penetration depth is ensured by acquiring data using a low frequency phased array transducer. Vascular pressure changes are then calculated from 2-D angle-independent vector velocity fields using a model based on the Navier-Stokes equations. Experimental scans are performed on a fabricated flow phantom having a constriction of 36% at a depth of 100 mm. Scans are carried out using a phased array transducer connected to the experimental scanner, SARUS. 2-D fields of angle-independent vector velocities are acquired using directional synthetic aperture vector flow imaging. The obtained results are evaluated by comparison to a 3-D numerical simulation model with equivalent geometry as the designed phantom. The study showed pressure drops across the constricted phantom varying from -40 Pa to 15 Pa with a standard deviation of 32%, and a bias of 25% found relative to the peak simulated pressure drop. This preliminary study shows that pressure can be estimated non-invasively to a depth that enables cardiac scans, and thereby, the possibility of detecting the pressure drops across the mitral valve.

This paper presents a novel automatic method for detection of B-lines (comet-tail artifacts) in lung ultrasound scans. B-lines are the most commonly used artifacts for analyzing the pulmonary edema. They appear as laser-like vertical beams, which arise from the pleural line and spread down without fading to the edge of the screen. An increase in their number is associated with presence of edema. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Denmark) driving a 192-element 5:5 MHz wide linear transducer (10L2W, BK Ultrasound). The dynamic received focus technique was employed to generate the sequences. Six subjects, among those three patients after major surgery and three normal subjects, were scanned once and Six ultrasound sequences each containing 50 frames were acquired. The proposed algorithm was applied to all 300 in-vivo lung ultrasound images. The pleural line is first segmented on each image and then the B-line artifacts spreading down from the pleural line are detected and overlayed on the image. The resulting 300 images showed that the mean lateral distance between B-lines detected on images acquired from patients decreased by 20% in compare with that of normal subjects. Therefore, the method can be used as the basis of a method of automatically and qualitatively characterizing the distribution of B-lines.

Excessive exposure to radiation increases the risk of cancer. We present the concept and design of a new imaging paradigm, X-ray induced acoustic computed tomography (XACT). Applying this innovative technology to breast imaging, one single X-ray exposure can generate a 3D acoustic image, which dramatically reduces the radiation dose to patients when compared to beast CT. A theoretical model is developed to analyze the sensitivity of XACT. A noise equivalent pressure model is used for calculating the minimal radiation dose in XACT imaging. Furthermore, K-Wave simulation is employed to study the acoustic wave propagation in breast tissue. Theoretical analysis shows that the X-ray induced acoustic signal has a 100% relative sensitivity to the X-ray absorption (given that the percentage change in the X-ray absorption coefficient yields the same percentage change in the acoustic signal amplitude), but not to X-ray scattering. The final detection sensitivity is primarily limited by the thermal noise. The radiation dose can be reduced by a factor of 100 compared with the newly FDA approved breast CT. Reconstruction result shows that breast calcification with diameter of 80 μm can be observed in XACT image by using ultrasound transducers with 5.5 MHz center frequency. Therefore, with the proposed innovative technology, one can potentially reduce radiation dose to patient in breast imaging as compared with current x-ray modalities.

Ultrasound modulated optical tomography (UMOT) combines high optical contrast with high ultrasound resolution to image soft tissues. A focused ultrasound beam introduced to a specific region of interest (ROI) in the object modulates the mean position of the scattering centers locally. This in turn modulates the overall decay of the specific intensity of an incident coherent light beam as it passes through the insonified region. The inverse problem of UMOT aims to recover the mean-squared displacements of the scattering centers from the measured amplitude autocorrelation of light. We propose an evolutionary Bayesian search scheme to invert the measurements through repeated solves of the correlation diffusion equation so as to drive the resultant measurement-prediction misfit to a zero-mean Brownian process. The discretized parameter vector evolves as a stochastic process with respect to an iteration variable and follows a recursive prediction-update algorithm. The conventional multiplicative-weight-based Bayesian update schemes suffer from sample degeneracy and are consequently ill-equipped to solve large dimensional problems in imaging. The key idea of this work is to incorporate a derivative-free additive correction to the predicted parameter process via a gain term that is functionally analogous to the weights. The numerical results for simulated data indicate that the proposed scheme substantively improves the reconstruction accuracy vis-à-vis a popularly adopted regularized Gauss-Newton approach. The advantage of a derivative-free scheme is particularly highlighted in cases characterized by low sensitivity of measurements to variations in the parameters. Moreover, the proposed scheme circumvents the tedious Jacobian calculations involved in a Gauss-Newton approach.

The aim of this study was to quantify the dosimetric effect of the AutoscanTM ultrasound probe, which is a 3D transperineal probe used for real-time tissue tracking during the delivery of radiotherapy. CT images of a solid water phantom, with and without the probe placed in contact with its surface, were obtained (0.75 mm slice width, 140 kVp). CT datasets were used for relative dose calculation in Monte Carlo simulations of a 7-field plan delivered to the phantom. The Monte Carlo software packages BEAMnrc and DOSXYZnrc were used for this purpose. A number of simulations, which varied the distance of the radiation field edge from the probe face (0 mm to 5 mm) were performed. Perineal surface doses as a function of distance from the radiation field edge, with and without the probe in place, were compared. The presence of the probe was found to result in negligible dose differences when the radiation field is not delivered through the probe. A maximum surface dose increase of ≈1% was found when the probe face to field edge distance was 0 mm. Surface doses with and without the probe in place agreed within Monte Carlo simulation uncertainty at distances ≥ 3 mm. Using data from three patient volunteers, a typical probe face to field edge distance was calculated to be ≈20 mm. Our results therefore indicate that the presence of the probe does not adversely affect a typical patient treatment, due to the relatively large probe face to field edge distance.

Enhanced blood perfusion in a tissue mass is an indication of neo-vascularity and a sign of a potential malignancy. Ultrasonic pulsed-Doppler imaging is a preferred modality for noninvasive monitoring of blood flow. However, the weak blood echoes and disorganized slow flow make it difficult to detect perfusion using standard methods without the expense and risk of contrast enhancement. Our research measures the efficiency of conventional power-Doppler (PD) methods at discriminating flow states by comparing measurement performance to that of an ideal discriminator. ROC analysis applied to the experimental results shows that power Doppler methods are just 30-50 % efficient at perfusion flows less than 1ml/min, suggesting an opportunity to improve perfusion assessment through signal processing. A new perfusion estimator is proposed by extending the statistical discriminator approach. We show that 2-D perfusion color imaging may be enhanced using this approach.

Ultrasound image quality enhancement is a problem of considerable interest in medical imaging modality and an ongoing challenge to date. This paper investigates a method based on frequency-shift low-pass filtering (FSLF) and least mean square adaptive filtering (LMSAF) for ultrasound image quality enhancement. FSLF is used for processing the ultrasound signal in the frequency domain, while LMSAPF in the time domain. Firstly, FSLF shifts the center frequency of the focused signal to zero. Then the real and imaginary part of the complex data are filtered respectively by finite impulse response (FIR) low-pass filter. Thus the information around the center frequency are retained while the undesired ones, especially background noises are filtered. Secondly, LMSAF multiplies the signals with an automatically adjusted weight vector to further eliminate the noises and artifacts. Through the combination of the two filters, the ultrasound image is expected to have less noises and artifacts and higher resolution, and contrast. The proposed method was verified with the RF data of the CIRS phantom 055A captured by SonixTouch DAQ system. Experimental results show that the background noises and artifacts can be efficiently restrained, the wire object has a higher resolution and the contrast ratio (CR) can be enhanced for about 12dB to 15dB at different image depth comparing to delay-and-sum (DAS).

Ultrasound imaging methods hold the potential to deliver low-cost, high-resolution, operator-independent and nonionizing imaging systems – such systems couple appropriate algorithms with imaging devices and techniques. The increasing demands on general practitioners motivate us to develop more usable and productive diagnostic imaging equipment. Ultrasound, specifically freehand ultrasound, is a low cost and safe medical imaging technique. It doesn't expose a patient to ionizing radiation. Its safety and versatility make it very well suited for the increasing demands on general practitioners, or for providing improved medical care in rural regions or the developing world. However it typically suffers from sonographer variability; we will discuss techniques to address user variability.

We also discuss our work to combine cylindrical scanning systems with state of the art inversion algorithms to deliver ultrasound systems for imaging and quantifying limbs in 3-D in vivo. Such systems have the potential to track the progression of limb health at a low cost and without radiation exposure, as well as, improve prosthetic socket fitting. Current methods of prosthetic socket fabrication remain subjective and ineffective at creating an interface to the human body that is both comfortable and functional. Though there has been recent success using methods like magnetic resonance imaging and biomechanical modeling, a low-cost, streamlined, and quantitative process for prosthetic cup design and fabrication has not been fully demonstrated. Medical ultrasonography may inform the design process of prosthetic sockets in a more objective manner. This keynote talk presents the results of progress in this area.

Conventional processes for prosthetic socket fabrication are heavily subjective, often resulting in an interface to the human body that is neither comfortable nor completely functional. With nearly 100% of amputees reporting that they experience discomfort with the wearing of their prosthetic limb, designing an effective interface to the body can significantly affect quality of life and future health outcomes. Active research in medical imaging and biomechanical tissue modeling of residual limbs has led to significant advances in computer aided prosthetic socket design, demonstrating an interest in moving toward more quantifiable processes that are still patient-specific. In our work, medical ultrasonography is being pursued to acquire data that may quantify and improve the design process and fabrication of prosthetic sockets while greatly reducing cost compared to an MRI-based framework. This paper presents a prototype limb imaging system that uses a medical ultrasound probe, mounted to a mechanical positioning system and submerged in a water bath. The limb imaging is combined with three-dimensional optical imaging for motion compensation. Images are collected circumferentially around the limb and combined into cross-sectional axial image slices, resulting in a compound image that shows tissue distributions and anatomical boundaries similar to magnetic resonance imaging. In this paper we provide a progress update on our system development, along with preliminary results as we move toward full volumetric imaging of residual limbs for prosthetic socket design. This demonstrates a novel multi-modal approach to residual limb imaging.

Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure and without treatment, can lead to death.

Clinically, 2D ultrasound (US) through the fontanelles ('soft spots') of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (CSF) ('ventricle tap', VT) might be indicated for a patient; however, quantitative measurements of the growth of the ventricles are often not performed. There is no consensus on when a neonate with PHVD should have an intervention and often interventions are performed after the potential for brain damage is quite high.

Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients.

We will describe the potential utility of quantitative 2D and 3D US to monitor and manage PHVD in neonates. Specifically, we will look to determine image-based measurement thresholds for patients who will require VT in comparison to patients with PHVD who resolve without intervention. Additionally, since many patients who have an initial VT will require subsequent interventions, we look at the potential for US to determine which PHVD patients will require additional VT after the initial one has been performed.

Recent literatures have reported that the targeted nanoscale ultrasound contrast agents are becoming more and more important in medical application, like ultrasound imaging, detection of perfusion, drug delivery and molecular imaging and so on. In this study, we fabricated an uniform nanoscale bubbles (257 nm with the polydispersity index of 0.458) by incorporation of antibody targeted to vascular endothelial growth factor receptor 2 (VEGFR2) into the nanobubbles membrane by using avidin-biotin interaction. Some fundamental characterizations such as nanobubble suspension, surface morphology, particle size distribution and zeta potential were investigated. The concentration and time-intensity curves (TICs) were obtained with a self-made ultrasound experimental setup in vitro evaluation. In addition, in order to evaluate the contrast enhancement ability and the potential tumor-targeted ability in vivo, normal Wistar rats and nude female BALB/c mice were intravascular administration of the nanobubbles via tail vein injection, respectively. Significant contrast enhancement of ultrasound imaging within liver and tumor were visualized. These experiments demonstrated that the targeted nanobubbles is efficient in ultrasound molecular imaging by enhancement of the contrast effect and have potential capacity for targeted tumor diagnosis and therapy in the future.

There is growing evidence that reverberation is a primary mechanism of clinical image degradation. This has led to a number of new approaches to suppress reverberation, including our recently proposed model-based algorithm. The algorithm can work well, but it must be trained to reject clutter, while preserving the signal of interest. One way to do this is to use simulated data, but current simulation methods that include multipath scattering are slow and do not readily allow separation of clutter and signal. Here, we propose a more convenient pseudo non-linear simulation method that utilizes existing linear simulation tools like Field II.

The approach functions by linearly simulating scattered wavefronts at shallow depths, and then time-shifting these wavefronts to deeper depths. The simulation only requires specification of the first and last scatterers encountered by a multiply reflected wave and a third point that establishes the arrival time of the reverberation. To maintain appropriate 2D correlation, this set of three points is fixed for the entire simulation and is shifted as with a normal linear simulation scattering field. We show example images, and we compute first order speckle statistics as a function of scatterer density. We perform ex vivo measures of reverberation where we find that the average speckle SNR is 1.73, which we can simulate with 2 reverberation scatterers per resolution cell. We also compare ex vivo lateral speckle statistics to those from linear and pseudo non-linear simulation data. Finally, the van Cittert-Zernike curve was shown to match empirical and theoretical observations.

Plane wave imaging is desirable for its ability to achieve high frame rates, allowing the capture of fast dynamic events, and continuous Doppler data. In most implementations of plane-wave imaging, multiple low resolution image (LRI) frames from different plane wave tilt angles are compounded to form a single high resolution image (HRI) frame, thereby reducing the frame rate. Compounding is a low-pass mean filter that causes attenuation and aliasing to signals with high Doppler shifts. On the other hand, the lateral beam profile and hence the quality of the HRI frames is improved by increasing the number of compounded frames. Therefore, a tradeoff exists between the Doppler limits and beam profile. In this paper, we present a method that eliminates this tradeoff and produces high resolution images without the use of compounding. The method suppresses the off-focus (clutter) signal by spreading its spectrum, while keeping the spectrum of the in-focus signal intact. The spreading is achieved by using a random sequence of tilt angles, as opposed to a linear sweep. Experiments performed using a carotid vessel phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and in particular outperforms conventional plane-wave Doppler at higher flow velocities. The spread-spectrum method is expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates.

When imaging with ultrasound through the chest wall, it is not uncommon for parts of the array to get blocked by ribs, which can limit the acoustic window and significantly impede visualization of the structures of interest. With the development of large-aperture, high-element-count, 2-D arrays and their potential use in transthoracic imaging, detecting and compensating for the blocked elements is becoming increasingly important.

We synthesized large coherent 2-D apertures and used them to image a point target through excised samples of canine chest wall. Blocked elements are detected based on low amplitude of their signals. As a part of compensation, blocked elements are turned off on transmit (Tx) and receive (Rx), and point-target images are created using: coherent summation of the remaining channels, compounding of intercostal apertures, and adaptive weighting of the available Tx/Rx channel-pairs to recover the desired k-space response. The adaptive compensation method also includes a phase aberration correction to ensure that the non-blocked Tx/Rx channel pairs are summed coherently.

To evaluate the methods, we compare the point-spread functions (PSFs) and near-field clutter levels for the transcostal and control acquisitions. Specifically, applying k-space compensation to the sparse aperture data created from the control acquisition reduces sidelobes from -6.6 dB to -12 dB. When applied to the transcostal data in combination with phase-aberration correction, the same method reduces sidelobes only by 3 dB, likely due to significant tissue induced acoustic noise. For the transcostal acquisition, turning off blocked elements and applying uniform weighting results in maximum clutter reduction of 5 dB on average, while the PSF stays intact. Compounding reduces clutter by about 3 dB while the k-space compensation increases clutter magnitude to the non-compensated levels.

This paper presents a work of real-time 3-D image reconstruction for a 7.5-MHz, 24×24 row-column addressing array transducer. The transducer works with a predesigned transmit/receive module. After the raw data are captured by the NI PXIe data acquisition (DAQ) module, the following processing procedures are performed: delay and sum (DAS), base-line calibration, envelope detection, logarithm compression, down-sampling, gray scale mapping and 3-D display. These procedures are optimized for obtaining real-time 3-D images. Fixed-point focusing scheme is applied in delay and sum (DAS) to obtain line data from channel data. Zero-phase high-pass filter is used to calibrate the base-line shift of echo. The classical Hilbert transformation is adopted to detect the envelopes of echo. Logarithm compression is implemented to enlarge the weak signals and narrow the gap from the strong ones. Down-sampling reduces the amount of data to improve the processing speed. Linear gray scale mapping is introduced that the weakest signal is mapped to 0 and the strongest signal 255. The real-time 3-D images are displayed with multi-planar mode, which shows three orthogonal sections (vertical section, coronal section, transverse section). A trigger signal is sent from the transmit/receive module to the DAQ module at the start of each volume data generation to ensure synchronization between these two modules. All procedures, include data acquisition (DAQ), signal processing and image display, are programmed on the platform of LabVIEW. 675MB raw echo data are acquired in one minute to generate 24×24×48, 27fps 3-D images. The experiment on the strong reflection object (aluminum slice) shows the feasibility of the whole process from raw data to real-time 3-D images.

The synthetic aperture (SA) technique can be used for achieving real-time volumetric ultrasound imaging using 2-D row-column addressed transducers. This paper investigates SA volumetric imaging performance of an in-house prototyped 3 MHz λ/2-pitch 62+62 element piezoelectric 2-D row-column addressed transducer array. Utilizing single element transmit events, a volume rate of 90 Hz down to 14 cm deep is achieved. Data are obtained using the experimental ultrasound scanner SARUS with a 70 MHz sampling frequency and beamformed using a delay-and-sum (DAS) approach. A signal-to-noise ratio of up to 32 dB is measured on the beamformed images of a tissue mimicking phantom with attenuation of 0.5 dB cm-1 MHz-1, from the surface of the probe to the penetration depth of 300λ. Measured lateral resolution as Full-Width-at-Half-Maximum (FWHM) is between 4λ and 10λ for 18% to 65% of the penetration depth from the surface of the probe. The averaged contrast is 13 dB for the same range. The imaging performance assessment results may represent a reference guide for possible applications of such an array in different medical fields.

Synthetic Aperture (SA) imaging produces high-quality images and velocity estimates of both slow and fast flow at high frame rates. However, grating lobe artifacts can appear both in transmission and reception. These affect the image quality and the frame rate. Therefore optimization of parameters effecting the image quality of SA is of great importance, and this paper proposes an advanced procedure for optimizing the parameters essential for acquiring an optimal image quality, while generating high resolution SA images. Optimization of the image quality is mainly performed based on measures such as F-number, number of emissions and the aperture size. They are considered to be the most contributing acquisition factors in the quality of the high resolution images in SA. Therefore, the performance of image quality is quantified in terms of full-width at half maximum (FWHM) and the cystic resolution (CTR). The results of the study showed that SA imaging with only 32 emissions and maximum sweep angle of 22 degrees yields a very good image quality compared with using 256 emissions and the full aperture size. Therefore the number of emissions and the maximum sweep angle in the SA can be optimized to reach a reasonably good performance, and to increase the frame rate by lowering the required number of emissions. All the measurements are performed using the experimental SARUS scanner connected to a λ/2-pitch transducer. A wire phantom and a tissue mimicking phantom containing anechoic cysts are scanned using the optimized parameters for the transducer. Measurements coincide with simulations.

This paper presents a novel beamformer architecture for a low-cost receiver front-end, and investigates if the image quality can be maintained. The system is oriented to the development of a hand-held wireless ultrasound probe based on Synthetic Aperture Sequential Beamforming, and has the advantage of effectively reducing circuit complexity and power dissipation. The array of transducers is divided into sub-apertures, in which the signals from the single channels are aligned through a network of cascaded gradient delays, and summed in the analog domain before A/D conversion. The delay values are quantized to simplify the shifting unit, and a single A/D converter is needed for each sub-aperture yielding a compact, low-power architecture that can be integrated in a single chip. A simulation study was performed using a 3:75MHz convex array, and the point spread function (PSF) for different configurations was evaluated in terms of lateral full-width-at-half-maximum (FWHM) and −20 dB cystic resolution (CR). Several setups were simulated varying the sub-aperture size N and the quantization step, and design constraints were obtained comparing the PSF to that of an ideal non-quantized system. The PSF is shown for N = 32 with a quantization step of 12 ns. For this configuration, the FWHM is degraded by 0.25% and the CR is 8.70% lower compared to the ideal situation. The results demonstrate that the gradient beamformer provides an adequate image quality, and open the way to a fully-integrated chip for a compact, low-cost, wireless ultrasound probe.

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

The word "Locomotive syndrome" has been proposed to describe the state of requiring care by musculoskeletal disorders and its high-risk condition. Reduction of the knee extension strength is cited as one of the risk factors, and the accurate measurement of the strength is needed for the evaluation. The measurement of knee extension strength using a dynamometer is one of the most direct and quantitative methods. This study aims to develop a system for measuring the knee extension strength using the ultrasound images of the rectus femoris muscles obtained with non-invasive ultrasonic diagnostic equipment. First, we extract the muscle area from the ultrasound images and determine the image features, such as the thickness of the muscle. We combine these features and physical features, such as the patient’s height, and build a regression model of the knee extension strength from training data. We have developed a system for estimating the knee extension strength by applying the regression model to the features obtained from test data. Using the test data of 168 cases, correlation coefficient value between the measured values and estimated values was 0.82. This result suggests that this system can estimate knee extension strength with high accuracy.

To diagnose heart valve incompetence, i.e., one of the most serious cardiac dysfunctions, it is essential to obtain images of fast-moving valves at high spatial and temporal resolution. Ultrasound synthetic transmit aperture (STA) imaging has the potential to achieve high spatial resolution by synthesizing multiple pre-beamformed images obtained with corresponding multiple transmissions. However, applying STA to fast-moving targets is difficult due to serious target deformation. We propose a high-frame-rate STA (fast STA) imaging method that uses a reduced number of transmission events needed for each image. Fast STA is expected to suppress deformation of moving targets; however, it may result in deteriorated spatial resolution. In this study, we conducted a simulation study to evaluate fast STA. We quantitatively evaluated the reduction in deformation and deterioration of spatial resolution with a model involving a radially moving valve at the maximum speed of 0.5 m/s. The simulated raw channel data of the valve phantom was processed with offline beamforming programs. We compared B-mode images obtained through single received-line in a transmission (SRT) method, STA, and fast STA. The results show that fast STA with four-times-reduced events is superior in reconstructing the original shape of the moving valve to other methods. The accuracy of valve location is 97 and 100% better than those with SRT and STA, respectively. The resolution deterioration was found to be below the annoyance threshold considering the improved performance of the shape reconstruction. The obtained results are promising for providing more precise diagnostic information on cardiovascular diseases.

Effect of echo artifacts on characterization of pulsatile tissues has been examined in neonatal cranial ultrasonic movies by characterizing pulsatile intensities with different regions of interest (ROIs). The pulsatile tissue, which is a key point in pediatric diagnosis of brain tissue, was detected from a heartbeat-frequency component in Fourier transform of a time-variation of 64 samples of echo intensity at each pixel in a movie fragment. The averages of pulsatile intensity and power were evaluated in two ROIs: common fan-shape and individual cranial-shape. The area of pulsatile region was also evaluated as the number of pixels where the pulsatile intensity exceeds a proper threshold. The extracranial pulsatile region was found mainly in the sections where mirror image was dominant echo artifact. There was significant difference of pulsatile area between two ROIs especially in the specific sections where mirror image was included, suggesting the suitability of cranial-shape ROI for statistical study on pulsatile tissues in brain. The normalized average of pulsatile power in the cranial-shape ROI exhibited most similar tendency to the normalized pulsatile area which was treated as a conventional measure in spite of its requirement of thresholding. It suggests the potential of pulsatile power as an alternative measure for pulsatile area in further statistical study of pulsatile tissues because it was neither affected by echo artifacts nor threshold.

Accurate extraction of cardiac fiber orientation from diffusion tensor imaging is important for determining heart structure and function. However, the acquisition of magnetic resonance (MR) diffusion tensor images is costly and time consuming. By comparison, cardiac ultrasound imaging is rapid and relatively inexpensive, but it lacks the capability to directly measure fiber orientations. In order to create a detailed heart model from ultrasound data, a three-dimensional (3D) diffusion tensor imaging (DTI) with known fiber orientations can be registered to an ultrasound volume through a geometric mask. After registration, the cardiac orientations from the template DTI can be mapped to the heart using a deformable transformation field. This process depends heavily on accurate fiber orientation extraction from the DTI. In this study, we use the FMRIB Software Library (FSL) to determine cardiac fiber orientations in diffusion weighted images. For the registration between ultrasound and MRI volumes, we achieved an average Dice similarity coefficient (DSC) of 81.6±2.1%. For the estimation of fiber orientations from the proposed method, we achieved an acute angle error (AAE) of 22.7±3.1° as compared to the direct measurements from DTI. This work provides a new approach to generate cardiac fiber orientation that may be used for many cardiac applications.

An investigation of several image reconstruction methods for robot-assisted ultrasound (US) tomography setup is presented. In the robot-assisted setup, an expert moves the US probe to the location of interest, and a robotic arm automatically aligns another US probe with it. The two aligned probes can then transmit and receive US signals which are subsequently used for tomographic reconstruction. This study focuses on reconstruction of the speed of sound. In various simulation evaluations as well as in an experiment with a millimeter-range inaccuracy, we demonstrate that the limited data provided by two probes can be used to reconstruct pixel-wise images differentiating between media with different speeds of sound. Combining the results of this investigation with the developed robot-assisted US tomography setup, we envision feasibility of this setup for tomographic imaging in applications beyond breast imaging, with potentially significant efficacy in cancer diagnosis.

Reflection image from ultrasound computed tomography (USCT) system can be obtained by synthetic aperture technique, however its quality is decreased by phase aberration caused by inhomogeneous media. Therefore, phase aberration correction is important to improve image quality. In this study, multi-stencils fast marching method (MSFMM) is employed for phase correction. The MSFMM is an accurate and fast solution of Eikonal equation which considers the refraction. The proposed method includes two steps. First, the MSFMM is used to compute sound propagation time from each element to each image gird point using sound speed image of USCT. Second, synthetic aperture technique is employed to obtain reflection image using the computed propagation time. To evaluate the proposed method, both numerical simulation and phantom experiment were conducted. With regard to numerical simulation, both quantitative and qualitative comparisons between reflection images with and without phase aberration correction were given. In the quantitative comparison, the diameters of point spread function (PSF) in reflection images of a two layer structure were presented. In the qualitative comparison, reflection images of simple circle and complex breast modes with phase aberration correction show higher quality than that without the correction. In respect to phantom experiment, a piece of breast phantom with artificial glandular structure inside was scanned by a USCT prototype, and the artificial glandular structure is able to be visible more clearly in the reflection image with phase aberration correction than in that without the correction. In this study, a phase aberration correction method by the MSFMM are proposed for reflection image of the USCT.

Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient’s breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.

Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.

Ultrasound (US) is the most commonly used liver imaging modality worldwide. It plays an important role in follow-up of cancer patients with liver metastases. We present an interactive segmentation approach for liver tumors in US acquisitions. Due to the low image quality and the low contrast between the tumors and the surrounding tissue in US images, the segmentation is very challenging. Thus, the clinical practice still relies on manual measurement and outlining of the tumors in the US images. We target this problem by applying an interactive segmentation algorithm to the US data, allowing the user to get real-time feedback of the segmentation results. The algorithm has been developed and tested hand-in-hand by physicians and computer scientists to make sure a future practical usage in a clinical setting is feasible. To cover typical acquisitions from the clinical routine, the approach has been evaluated with dozens of datasets where the tumors are hyperechoic (brighter), hypoechoic (darker) or isoechoic (similar) in comparison to the surrounding liver tissue. Due to the interactive real-time behavior of the approach, it was possible even in difficult cases to find satisfying segmentations of the tumors within seconds and without parameter settings, and the average tumor deviation was only 1.4mm compared with manual measurements. However, the long term goal is to ease the volumetric acquisition of liver tumors in order to evaluate for treatment response. Additional aim is the registration of intraoperative US images via the interactive segmentations to the patient's pre-interventional CT acquisitions.

One technique used to infer and monitor patient's respiratory conditions is the electrical impedance tomography (EIT). This provides images with information about lung function. The EIT image contrast is dependent on the variation of electrical impedance, therefore, this image does not provide anatomical details in border regions of several organs. To contribute to a clinical solution, we propose a new method to delimit regions of interest such as the pulmonary region and to improve the reconstruction quality of the EIT. Using a Matlab Toolbox k-wave, the ultrasound propagation phenomenon in homogeneous medium without patient (Reference) and with thoracic models were simulated, separately via a set of several ultrasound transducers distributed around the chest. After pulse emission by a transducer (TR), all received signals were compared considering the two sets of signals. If the energy relation between parts of the signals does not exceed an empirical threshold (30% in this study), a partial mask is generated between the transmitter and the receptor. This process was repeated until all 128 transducers are considered as TR-emitters. The 128 transducers (150kHz) are uniformly distributed. The evaluation was made by visually comparing the resulting images with the respective simulated object. A simple approach was presented to delimit high contrast organs with ultrasound transducers distributed around the patient. This approach allows other lower contrast objects to become invisible by varying the threshold limit. The investigation, based on numerical simulations of ultrasonic propagation, has shown promising results in the delimitation of the pulmonary region.

During manual palpation of breast masses, the perception of its stiffness and slipperiness are the two commonly used information by the physician. In order to reliably and quantitatively obtain this information several non-invasive elastography techniques have been developed that seek to provide an image of the underlying mechanical properties, mostly stiffness-related. Very few approaches have visualized the "slip" at the lesion-background boundary that only occurs for a loosely-bonded benign lesion. It has been shown that axial-shear strain distribution provides information about underlying slip. One such feature, referred to as "fill-in" was interpreted as a surrogate of the rotation undergone by an asymmetrically-oriented-loosely bonded-benign-lesion under quasi-static compression. However, imaging and direct visualization of the rotation itself has not been addressed yet. In order to accomplish this, the quality of lateral displacement estimation needs to be improved. In this simulation study, we utilize spatial compounding approach and assess the feasibility to obtain good quality rotation elastogram. The angular axial and lateral displacement estimates were obtained at different insonification angles from a phantom containing an elliptical inclusion oriented at 45°, subjected to 1% compression from the top. A multilevel 2D-block matching algorithm was used for displacement tracking and 2D-least square compounding of angular axial and lateral displacement estimates was employed. By varying the maximum steering angle and incremental angle, the improvement in the lateral motion tracking accuracy and its effects on the quality of rotational elastogram were evaluated. Results demonstrate significantly-improved rotation elastogram using this technique.

Ultrasound Elastography is an emerging imaging technique that allows estimation of the mechanical characteristics of tissue. Two issues that need to be addressed before widespread use of elastography in clinical environments are real time constraints and deteriorating effects of signal decorrelation between pre- and post-compression images. Previous work has used Dynamic Programming (DP) to estimate tissue deformation. However, in case of large signal decorrelation, DP can fail. In this paper we, have proposed a novel solution to this problem by solving DP on a tree instead of a single Radio-Frequency line. Formulation of DP on a tree allows exploiting significantly more information, and as such, is more robust and accurate. Our results on phantom and in-vivo human data show that DP on tree significantly outperforms traditional DP in ultrasound elastography.

Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.